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Swinton, PA, Lloyd, R, Keogh, JWL, Agouris, I, and Stewart, AD. A biomechanical comparison of the traditional squat, powerlifting squat, and box squat. J Strength Cond Res 26(7): 1805-1816, 2012. The purpose of this study was to compare the biomechanics of the traditional squat with 2 popular exercise variations commonly referred to as the powerlifting squat and box squat. Twelve male powerlifters performed the exercises with 30, 50, and 70% of their measured 1 repetition maximum (1RM), with instruction to lift the loads as fast as possible. Inverse dynamics and spatial tracking of the external resistance were used to quantify biomechanical variables. A range of significant kinematic and kinetic differences (p , 0.05) emerged between the exercises. The traditional squat was performed with a narrow stance, whereas the powerlifting squat and box squat were performed with similar wide stances (48.3 6 3.8, 89.6 6 4.9, 92.1 6 5.1 cm, respectively). During the eccentric phase of the traditional squat, the knee traveled past the toes resulting in anterior displacement of the system center of mass (COM). In contrast, during the powerlifting squat and box squat, a more vertical shin position was maintained, resulting in posterior displacements of the system COM. These differences in linear displacements had a significant effect (p , 0.05) on a number of peak joint moments, with the greatest effects measured at the spine and ankle. For both joints, the largest peak moment was produced during the traditional squat, followed by the powerlifting squat, then box squat. Significant differences (p , 0.05) were also noted at the hip joint where the largest moment in all 3 planes were produced during the powerlifting squat. Coaches and athletes should be aware of the biomechanical differences between the squatting variations and select according to the kinematic and kinetic profile that best match the training goals.

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Background Diabetes mellitus patients are at increased risk of developing diabetic foot with peripheral neuropathy, vascular and musculoskeletal complications. Therefore they are prone to develop frequent and often foot problems with a relative high risk of infection, gangrene and amputation. In addition, altered plantar pressure distribution is an important etiopathogenic risk factor for the development of foot ulcers. Thus the review on study of foot kinematic and kinetic in type 2 diabetes mellitus to understand the biomechanical changes is important.Methodology Scientific articles were obtained using electronic databases including Science Direct, CINAHL, Springer Link, Medline, Web of Science, and Pubmed. The selection was completed after reading the full texts. Studies using experimental design with focus on biomechanics of diabetic foot were selected.ResultsThe meta-analysis report on gait velocity (neuropathy = 128 and non-diabetes = 131) showed that there was a significantly lower gait velocity in neuropathy participants compared to non-diabetes age matched participants at a high effect level (−0.09, 95 % CI −0.13 to 0.05; p < 0.0001). Regarding knee joint flexion range there was a significant difference between neuropathy and non-diabetes group (4.75, 95 % CI, −7.53 to 1.97, p = 0.0008).ConclusionsThe systematic review with meta-analysis reported significant difference in kinematic and kinetic variables among diabetic with neuropathy, diabetic without neuropathy and non-diabetes individuals. The review also found that the sample size in some studies were not statistically significant to perform the meta-analysis and report a strong conclusion. Therefore a study with higher sample size should be done.

It was the aim of the present study to expand on previous correlation analyses that have attempted to identify factors that influence performance of jumping, sprinting, and changing direction. This was achieved by using a regression approach to obtain linear models that combined anthropometric, strength, and other biomechanical variables. Thirty rugby union players participated in the study (age: 24.2 ± 3.9 years; stature: 181.2 ± 6.6 cm; mass: 94.2 ± 11.1 kg). The athletes' ability to sprint, jump, and change direction was assessed using a 30-m sprint, vertical jump, and 505 agility test, respectively. Regression variables were collected during maximum strength tests (1 repetition maximum [1RM] deadlift and squat) and performance of fast velocity resistance exercises (deadlift and jump squat) using submaximum loads (10-70% 1RM). Force, velocity, power, and rate of force development (RFD) values were measured during fast velocity exercises with the greatest values produced across loads selected for further analysis. Anthropometric data, including lengths, widths, and girths were collected using a 3-dimensional body scanner. Potential regression variables were first identified using correlation analyses. Suitable variables were then regressed using a best subsets approach. Three factor models generally provided the most appropriate balance between explained variance and model complexity. Adjusted R values of 0.86, 0.82, and 0.67 were obtained for sprint, jump, and change of direction performance, respectively. Anthropometric measurements did not feature in any of the top models because of their strong association with body mass. For each performance measure, variance was best explained by relative maximum strength. Improvements in models were then obtained by including velocity and power values for jumping and sprinting performance, and by including RFD values for change of direction performance.